AUTHOR=Xiao Zhenlong , Wang Xin , Hong Lin 

TITLE=Cellular reaction gene regulation network for swarm robots with pattern formation maneuvering control

JOURNAL=Frontiers in Neurorobotics

VOLUME=Volume 16 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/neurorobotics/articles/10.3389/fnbot.2022.950572

DOI=10.3389/fnbot.2022.950572

ISSN=1662-5218

ABSTRACT=Self-organized pattern formation enables swarm robots to interact with local environments to self-organize into intricate structures generated by gene regulatory network (GRN) control methods without global knowledge.
Previous studies have reported that it is challenging to maintain pattern formation stability during maneuvering in the environment due to local morphogenetic reaction rules. 
Motivated by the mechanism of the GRN in \textit{multi-cellular organisms}, we propose a novel cellular reaction gene regulatory network (CR-GRN) for pattern formation maneuvering control.
The CR-GRN depicts the robots, environment, virtual target pattern, and interaction by a cellular reaction network to generate emergent swarm behavior in multi-robot systems. 
Instead of the traditional differential equation, a static diffusion function is proposed to simulate the process of morphogen diffusion among cells to ensure stable adaptive pattern generation. 
In addition, genes, proteins, and morphogens are used to define the internal and external states of cells and form a feedback regulation network.
Simulation experiments are conducted to validate the proposed method. The results show that the CR-GRN can satisfy the requirements of turning curvature and maintain the robot's uniformity based on the proposed algorithm. 
This proves that robots using the CR-GRN can cooperate more effectively to cope in a complicated environment, and maintain a stable formation during maneuvering.